1. Field of the Invention
The present invention relates in general to the field of pattern recognition and, more particularly, to a learning method for a pattern recognition system, to a method for re-recognizing at least one pattern, to a pattern recognition system and to the use of such a pattern recognition system.
2. Description of the Related Art
Pattern recognition herein refers to predetermined patterns to be re-recognized which are fed in advance to a technical system or, in other words, that the pattern recognition system is trained. The pattern recognition system is intended to re-recognize later these patterns on which it has been trained in advance.
In this case, “pattern” in the meaning of the present invention is to be understood as any two-dimensional or multidimensional representation of sensory impressions. Patterns in the meaning of the present invention can therefore naturally be images of physical objects. Further sensory impressions can be smell or sound signals. In the case of sound signals, the two-dimensional representation can be, for example, a frequency spectrum or the amplitude characteristic as a function of time.
There are, of course, many concrete applications of pattern recognition. Mention may be made, as an example, of, on the one hand, robotics, the pattern recognition system in this case serving the purpose of having the robot pick up predetermined objects (which in this case represent the trained patterns), for example from an assembly line or the like.
A further possible field of application is represented in general by medical technology. For example, the pattern recognition system can recognize tumor diseases on images of medical imaging systems when the pattern recognition system has been trained on typical syndromes of tumors as patterns.
In an application to acoustic signals, a pattern recognition system can recognize, for example, trained sounds in a noisy spectrum.
A substantial point with regard to the technical implementation of a pattern recognition system is the way in which the information that is reproduced in the pattern is fed to the pattern recognition system. It is known in this case from the prior art to implement such technical systems by what is termed a feed-forward approach such as is explained, for example, in Marr, “Vision: A Computational Investigation into the human Representation and Processing of visual Information”, New York, Freeman, 1982. Feed-forward means in essence in this case that only information on the pattern to be recognized is processed, in particular in the recognition phase of pattern recognition. It has emerged in the meantime that this feed-forward approach is inadequate in the case of technical implementation in that the resulting processing speeds are too slow.